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def tag_ru_files(predictor: RNNMorphPredictor) -> Dict:
if not os.path.exists(TEST_TAGGED_FOLDER):
os.makedirs(TEST_TAGGED_FOLDER)
tag(predictor, TEST_UNTAGGED_LENTA, TEST_TAGGED_LENTA)
tag(predictor, TEST_UNTAGGED_VK, TEST_TAGGED_VK)
tag(predictor, TEST_UNTAGGED_JZ, TEST_TAGGED_JZ)
quality = dict()
print("Lenta:")
quality['Lenta'] = measure(TEST_GOLD_LENTA, TEST_TAGGED_LENTA, True, None)
print("VK:")
quality['VK'] = measure(TEST_GOLD_VK, TEST_TAGGED_VK, True, None)
print("JZ:")
quality['JZ'] = measure(TEST_GOLD_JZ, TEST_TAGGED_JZ, True, None)
print("All:")
count_correct_tags = quality['Lenta'].correct_tags + quality['VK'].correct_tags + quality['JZ'].correct_tags
count_correct_pos = quality['Lenta'].correct_pos + quality['VK'].correct_pos + quality['JZ'].correct_pos
count_tags = quality['Lenta'].total_tags + quality['VK'].total_tags + quality['JZ'].total_tags
count_correct_sentences = quality['Lenta'].correct_sentences + quality['VK'].correct_sentences + \
quality['JZ'].correct_sentences
count_sentences = quality['Lenta'].total_sentences + quality['VK'].total_sentences + \
quality['JZ'].total_sentences
quality['All'] = dict()
quality['All']['tag_accuracy'] = float(count_correct_tags) / count_tags
quality['All']['pos_accuracy'] = float(count_correct_pos) / count_tags
quality['All']['sentence_accuracy'] = float(count_correct_sentences) / count_sentences
return quality